Interoceptive machine framework: Toward interoception-inspired regulatory architectures in artificial intelligence

ArXi:2604.24527v1 Announce Type: new This review proposes an integrative framework grounded on interoception and embodied AI-termed the interoceptive machine framework-that translates biologically inspired principles of internal-state regulation into computational architectures for adaptive autonomy. Interoception, conceived as the monitoring, integration, and regulation of internal signals, has proven relevant for understanding adaptive behavior in biological systems.